Abstract

The application of neural network with back propagation algorithm in field of forecasting is now widely used. However,there are few factors that must be looked into in order to produce a network that will converge and generalize. Basically the learning process of a network is influenced by value of momentum constant,learning rate parameter,number of hidden nodes and selected transfer
function. Inappropriate choose of value will result in network not reaching the targeted value. Effects of data transformation and stationary data on the ability of
the network to converge and generalize also will be studied. The arrival of tourist to Langkawi by ferry, cruise and flight are used as a case study for this project.
Neural network models are built using Matlab 6.1 and Statistica is used to make data stationary.